Due to the escalation in the rate of crimes, there is a requirement of the system that will detect and predict crimes at the dynamic time. The objective of this survey is to learn Data Mining techniques that will go on to help in detecting and predicting crimes using association rule mining, decision trees & naive Bayes, k-means clustering and Machine learning techniques such as deep neural network and artificial neural network. Noticeable findings from this survey were that when the dataset instances have a large number of missing values pre-processing becomes an important task and crime does not occur uniformly across urban landscapes but concentrates in specific areas. Hence, predicting crime hotspots is a very crucial task and also applying post-processing will help in decreasing the rate of crimes.